AnalyseMorphologique/utils/math/data_extraction.py

140 lines
3.8 KiB
Python

"""
Created on Mon Apr 17 2023
@name: data_extraction.py
@desc: This module contains some utility functions for math operations.
@auth: Djalim Simaila
@e-mail: djalim.simaila@inrae.fr
"""
import numpy as np
import math
def get_mean(values:list):
"""
Get the mean of the values.
:param values: values
:return: mean of the values
:Example:
>>> get_mean([1,2,3,4,5])
3.0
"""
return np.mean(values)
def get_standard_deviation(values:list):
"""
Get the standard deviation of the values.
:param values: values
:return: standard deviation of the values
:Example:
>>> get_standard_deviation([1,2,3,4,5])
1.4142135623730951
"""
return np.std(values)
def get_x_y_z_mean(discrete_values:list):
"""
Get the mean of the x and y coordinates in the discrete range.
:param x: x coordinates
:param y: y coordinates
:return: mean of x and y coordinates in the discrete range
:Example:
>>> get_x_y_z_mean([(1,2,3),(4,5,6),(7,8,9)])
(4.0, 5.0, 6.0)
"""
x = [vertex[0] for vertex in discrete_values]
y = [vertex[1] for vertex in discrete_values]
z = [vertex[2] for vertex in discrete_values]
return get_mean(x), get_mean(y), get_mean(z)
def get_radius_from_x_y(xi:float, yi:float, x_mean:float, y_mean:float):
"""
Get the radius from the x and y coordinates.
:param xi: x coordinate
:param yi: y coordinate
:param x_mean: mean of x coordinates in the discrete range
:param y_mean: mean of y coordinates in the discrete range
:return: radius for this point
:Example:
>>> get_radius_from_x_y(1,2,3,4)
2.8284271247461903
"""
return np.sqrt(np.power((xi - x_mean), 2) + np.power((yi - y_mean), 2))
def get_mean_radius(discrete_values:list):
"""
Get the mean of the radius in the discrete range.
:param discrete_values: discrete values
:return: mean of the radius in the discrete range
:Example:
>>> get_mean_radius([(1,2,3),(4,5,6),(7,8,9)])
2.82842712474619
"""
x_mean, y_mean, z_mean = get_x_y_z_mean(discrete_values)
radius = []
for x,y,z in discrete_values:
radius.append(get_radius_from_x_y(x,y,x_mean,y_mean))
return get_mean(radius)
def get_radius_std(discrete_values:list):
"""
Get the standard deviation of the radius in the discrete range.
:param discrete_values: discrete values
:return: standard deviation of the radius in the discrete range
:Example:
>>> get_radius_std([(1,2,3),(4,5,6),(7,8,9)])
2.8284271247461903
"""
x_mean, y_mean, z_mean = get_x_y_z_mean(discrete_values)
radius = []
for x,y,z in discrete_values:
radius.append(get_radius_from_x_y(x,y,x_mean,y_mean))
return get_standard_deviation(radius)
def get_mean_teta(discrete_values:list):
"""
Get the mean of the teta in the discrete range.
:param discrete_values: discrete values
:return: mean of the teta in the discrete range
:Example:
>>> get_mean_teta([(1,2,3),(4,5,6),(7,8,9)])
0.7853981633974483
"""
x_mean, y_mean, z_mean = get_x_y_z_mean(discrete_values)
teta = []
for x,y,z in discrete_values:
teta.append(get_teta_from_x_y(x,y,x_mean,y_mean))
return get_mean(teta)
def get_teta_from_x_y(xi:float, yi:float, x_mean:float, y_mean:float):
"""
Get the teta from the x and y coordinates.
:param xi: x coordinate
:param yi: y coordinate
:param x_mean: mean of x coordinates in the discrete range
:param y_mean: mean of y coordinates in the discrete range
:return: teta for this point
:Example:
>>> get_teta_from_x_y(1,2,3,4)
0.7853981633974483
"""
return math.atan((xi - x_mean)/(yi - y_mean))
#todo fix examples
if __name__ == "__main__":
import doctest
doctest.testmod()